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To evaluate the feasibility ofA framework for sodium relaxometry using MRF at 7T was developed, allowing simultaneous measurement of relaxation times and inhomogeneities in the static field. The technique distinguishes between bi- and monoexponential transverse relaxation and was validated in simulations with respect to the ground truth. In phantom measurements, a resolution of 2 × 2 × 12 mmPhantom experiments revealed an agreement between the relaxation times obtained viaThis work demonstrates the feasibility of

To quantify the tissue sodium concentration (TSC) in cardiacWithout any correction the measured myocardial TSC was (54 ± 5) mM. The applied correction methods reduced these values by (48 ± 5)% to (29 ± 3) mM, where PV correction had the largest effect (reduction of (34 ± 1)%). Respiratory and cardiac motion gating decreased the concentrations by (11 ± 1)%. With the applied setup, the corrections of BFor quantitative human cardiac

To investigate and to reduce influences on the determination of the short and long apparent transverse relaxation times ( T2,s*, T2,l*) ofThe accuracy of T2* determination was analyzed in simulations for five different sampling schemes. The influence of noise in the parameter fit was investigated for three different models. A dedicated sampling scheme was developed for brain parenchyma by numerically optimizing the parameter estimation. This scheme was compared in vivo to linear sampling at 7T.For the considered sampling schemes, T2,s* / T2,l* exhibit an average bias of 3% / 4% with a variation of 25% / 15% based on simulations with previously published T2* values. The accuracy could be improved with the optimized sampling scheme by strongly averaging the earliest sample. A fitting model with constant noise floor can increase accuracy while additional fitting of a noise term is only beneficial in case of sampling until late echo time 80 ms. T2* values in white matter were determined to be T2,s* = 5.1 ± 0.8 / 4.2 ± 0.4 ms and T2,l* = 35.7 ± 2.4 / 34.4 ± 1.5 ms using linear/optimized sampling.Voxel-wise T2* determination of

To assess the reproducibility ofDynamicComparison with the ground truth of simulations revealed improved CMROThis in vivo

The purpose of this study is to improve direct phosphorus (

To reduce noise and artifacts in (23)Na MRI with a Compressed Sensing reconstruction and a learned dictionary as sparsifying transform.A three-dimensional dictionary-learning compressed sensing reconstruction algorithm (3D-DLCS) for the reconstruction of undersampled 3D radial (23)Na data is presented. The dictionary used as the sparsifying transform is learned with a K-singular-value-decomposition (K-SVD) algorithm. The reconstruction parameters are optimized on simulated data, and the quality of the reconstructions is assessed with peak signal-to-noise ratio (PSNR) and structural similarity (SSIM). The performance of the algorithm is evaluated in phantom and in vivo (23)Na MRI data of seven volunteers and compared with nonuniform fast Fourier transform (NUFFT) and other Compressed Sensing reconstructions.The reconstructions of simulated data have maximal PSNR and SSIM for an undersampling factor (USF) of 10 with numbers of averages equal to the USF. For 10-fold undersampling, the PSNR is increased by 5.1 dB compared with the NUFFT reconstruction, and the SSIM by 24%. These results are confirmed by phantom and in vivo (23)Na measurements in the volunteers that show markedly reduced noise and undersampling artifacts in the case of 3D-DLCS reconstructions.The 3D-DLCS algorithm enables precise reconstruction of undersampled (23)Na MRI data with markedly reduced noise and artifact levels compared with NUFFT reconstruction. Small structures are well preserved.

Amide protons of peptide bonds induce an important chemical exchange saturation transfer (CEST) contrast in vivo. As a simple in vitro model for a peptide amide proton CEST effect, we suggest herein the dipeptide carnosine. We show that the metabolite carnosine creates a CEST effect and we study the properties of the exchange of the amide proton (-NH) of the carnosine peptide bond (NHCPB) in model solutions for a pH range from 6 to 8.3 and a temperature range from T = 5 °C to 43 °C by means of CEST and water exchange spectroscopy (WEX) experiments on a 3 T whole-body MR tomograph. The dependence of the NHCPB chemical exchange rate k(sw) on pH and temperature T was determined using WEX. For physiological conditions (T = 37 °C, pH = 7.10) we obtained k(sw) = (47.07 ± 7.90)/s. With similar chemical shift and exchange properties to amide protons in vivo, carnosine forms a simple model system for optimization of CEST pulse sequences in vitro. The potential for direct detection of the metabolite carnosine in vivo is discussed.

To increase the signal-to-noise ratio (SNR) and to reduce artifacts in non-proton magnetic resonance imaging (MRI) by incorporation of a priori information from (1) H MR data in an iterative reconstruction.An iterative reconstruction algorithm for 3D projection reconstruction (3DPR) is presented that combines prior anatomical knowledge and image sparsity under a total variation (TV) constraint. A binary mask (BM) is used as an anatomical constraint to penalize non-zero signal intensities outside the object. The BMTV method is evaluated in simulations and in MR measurements in volunteers.In simulated BMTV brain data, the artifact level was reduced by 20% while structures were well preserved compared to gridding. SNR maps showed a spatially dependent SNR gain over gridding reconstruction, which was up to 100% for simulated data. Undersampled 3DPR (23) Na MRI of the human brain revealed an SNR increase of 29 ± 7%. Small anatomical structures were reproduced with a mean contrast loss of 14%, whereas in TV-regularized iterative reconstructions a loss of 66% was found.The BMTV algorithm allows reconstructing images with increased SNR and reduced artifact level compared to gridding and performs superior to an iterative reconstruction using an unspecific TV constraint only.